ESAIM Probability and Statistics · 2010 · 11 citations · 8 references
Natural SciencesComputer ScienceData StructuresProbability TheoryStochastic ProcessesCoding TheoryGraph TheoryNetwork StructureNetwork TheoryProbabilistic CombinatoricsStochastic NetworksAsymptotic Equipartition PropertyAsymptotic PropertiesGalton-watson TreesHierarchical StructuresLarge Deviation PrinciplesRandom Graph ModelsRandom Graph TheoryRandom Graphs
We prove asymptotic equipartition properties for simple hierarchical structures (modelled as multitype Galton-Watson trees) and networked structures (modelled as randomly coloured random graphs). For example, for large n, a networked data structure consisting of n units connected by an average number of links of order n / log n can be coded by about H × n bits, where H is an explicitly defined entropy. The main technique in our proofs are large deviation principles for suitably defined empirical measures.
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Random graphs as models of networks
M. E. J. Newman · arXiv (Cornell University) · 2002 · 242 citations · Full text
Life Sciences, Infectious Disease Control, Computer Networks +15
J. D. Biggins · Electronic Communications in Probability · 2004 · 36 citations · Full text